matplotlib-users Mailing List for matplotlib

>>>>> "Christopher" == Christopher Barker <Chr...@no...> writes:
 Christopher> This sounds like a job for properties! make
 Christopher> _transform a property, and code that gets and sets it
 Christopher> directly should still work. though People that were
 Christopher> accessing an underscored name directly should expect
 Christopher> this kind of problem.
The matplotlib artist kwarg properties act like python properties or
enthought traits, with some advantages and disadvantages over each
(mostly disadvantages, alas). We've discussed migrating to one or
another over the years, but haven't bitten the bullet. At each point
it's easier to extend the exiting implementation than refactor the
whole bit; the tyranny of small decisions.
Here are some of the pros and cons as I see them of enthought traits
vs python properties
 Pros:
 * compatibility with the rest of the enthought tool suite
 * built in observer pattern
 * automatic UI for wx users
 * performance is better than python properties last time I looked
 * matplotlib ships with enthought traits built in 
 Cons:
 * smaller user base than python properties may imply
 fewer 3rd party enhancements, less support, etc
 * we have to maintain our copy of enthought traits to keep it
 current and building or require an additional dependency
I spent some time working on matplotlib rc properties as enthought
traits as a precursor to porting matplotlib properties to traits.
Here is some example code showing how to define some representative rc
properties and construct a matplotlib artist using traits. Because
matplotlib ships with enthought traits already, you can run this
script with just matplotlib. Unfortunately, we do not ship the ex UI
component so you can't test that part. I'm a bit of a traits newbie
so there are probably better ways to do what I have done below.
import sys, os, re
import matplotlib.enthought.traits as traits
from matplotlib.cbook import is_string_like
from matplotlib.artist import Artist
doprint = True
flexible_true_trait = traits.Trait(
 True, 
 { 'true': True, 't': True, 'yes': True, 'y': True, 'on': True, True: True,
 'false': False, 'f': False, 'no': False, 'n': False, 'off': False, False: False
 } )
flexible_false_trait = traits.Trait( False, flexible_true_trait )
colors = {
 'c' : '#00bfbf',
 'b' : '#0000ff',
 'g' : '#008000',
 'k' : '#000000',
 'm' : '#bf00bf',
 'r' : '#ff0000',
 'w' : '#ffffff',
 'y' : '#bfbf00',
 'gold' : '#FFD700',	
 'peachpuff' : '#FFDAB9',	
 'navajowhite' : '#FFDEAD',	
 }
def hex2color(s):
 "Convert hex string (like html uses, eg, #efefef) to a r,g,b tuple"
 return tuple([int(n, 16)/255.0 for n in (s[1:3], s[3:5], s[5:7])])
class RGBA(traits.HasTraits):
 # r,g,b,a in the range 0-1 with default color 0,0,0,1 (black)
 r = traits.Range(0., 1., 0.)
 g = traits.Range(0., 1., 0.)
 b = traits.Range(0., 1., 0.)
 a = traits.Range(0., 1., 1.)
 def __init__(self, r=0., g=0., b=0., a=1.):
 self.r = r
 self.g = g
 self.b = b
 self.a = a
 def __repr__(self):
 return 'r,g,b,a = (%1.2f, %1.2f, %1.2f, %1.2f)'%\
 (self.r, self.g, self.b, self.a)
def tuple_to_rgba(ob, name, val):
 tup = [float(x) for x in val]
 if len(tup)==3:
 r,g,b = tup
 return RGBA(r,g,b)
 elif len(tup)==4:
 r,g,b,a = tup
 return RGBA(r,g,b,a)
 else:
 raise ValueError
tuple_to_rgba.info = 'a RGB or RGBA tuple of floats'
def hex_to_rgba(ob, name, val):
 rgx = re.compile('^#[0-9A-Fa-f]{6}$')
 if not is_string_like(val):
 raise TypeError
 if rgx.match(val) is None:
 raise ValueError
 r,g,b = hex2color(val)
 return RGBA(r,g,b,1.0)
hex_to_rgba.info = 'a hex color string'
def colorname_to_rgba(ob, name, val):
 hex = colors[val.lower()]
 r,g,b = hex2color(hex)
 return RGBA(r,g,b,1.0)
colorname_to_rgba.info = 'a named color'
def float_to_rgba(ob, name, val):
 val = float(val)
 return RGBA(val, val, val, 1.)
float_to_rgba.info = 'a grayscale intensity'
Color = traits.Trait(RGBA(), float_to_rgba, colorname_to_rgba, RGBA,
 hex_to_rgba, tuple_to_rgba)
def file_exists(ob, name, val):
 fh = file(val, 'r')
 return val
def path_exists(ob, name, val):
 os.path.exists(val)
linestyles = ('-', '--', '-.', ':', 'steps', 'None')
TICKLEFT, TICKRIGHT, TICKUP, TICKDOWN = range(4)
linemarkers = (None, '.', ',', 'o', '^', 'v', '<', '>', 's',
 '+', 'x', 'd', 'D', '|', '_', 'h', 'H',
 'p', '1', '2', '3', '4',
 TICKLEFT,
 TICKRIGHT,
 TICKUP,
 TICKDOWN,
 'None'
 )
class LineRC(traits.HasTraits):
 linewidth = traits.Float(0.5) 
 linestyle = traits.Trait(*linestyles)
 color = Color
 marker = traits.Trait(*linemarkers)
 markerfacecolor = Color
 markeredgecolor = Color 
 markeredgewidth = traits.Float(0.5)
 markersize = traits.Float(6) 
 antialiased = flexible_true_trait 
 data_clipping = flexible_false_trait 
class PatchRC(traits.HasTraits):
 linewidth = traits.Float(1.0) 
 facecolor = Color
 edgecolor = Color 
 antialiased = flexible_true_trait 
timezones = 'UTC', 'US/Central', 'ES/Eastern' # fixme: and many more
backends = ('GTKAgg', 'Cairo', 'FltkAgg', 'GD', 'GDK', 'GTK', 'Agg',
 'GTKCairo', 'Paint', 'PS', 'SVG', 'Template', 'TkAgg',
 'WX')
class RC(traits.HasTraits):
 backend = traits.Trait(*backends)
 numerix = traits.Trait('Numeric', 'numarray')
 interactive = flexible_false_trait
 toolbar = traits.Trait('toolbar2', 'classic', None)
 timezone = traits.Trait(*timezones)
 lines = traits.Trait(LineRC())
 patch = traits.Trait(PatchRC())
rc = RC()
rc.lines.color = 'r'
if doprint:
 print 'RC'
 rc.print_traits()
 print 'RC lines'
 rc.lines.print_traits()
 print 'RC patches'
 rc.patch.print_traits()
class Patch(Artist, traits.HasTraits):
 linewidth = traits.Float(0.5)
 facecolor = Color
 fc = facecolor
 edgecolor = Color
 fill = flexible_true_trait
 def __init__(self,
 edgecolor=None, 
 facecolor=None,
 linewidth=None,
 antialiased = None, 
 fill=1,
 **kwargs
 ):
 Artist.__init__(self)
 if edgecolor is None: edgecolor = rc.patch.edgecolor
 if facecolor is None: facecolor = rc.patch.facecolor
 if linewidth is None: linewidth = rc.patch.linewidth
 if antialiased is None: antialiased = rc.patch.antialiased
 self.edgecolor = edgecolor
 self.facecolor = facecolor
 self.linewidth = linewidth
 self.antialiased = antialiased 
 self.fill = fill
 
p = Patch()
p.facecolor = '#bfbf00'
p.edgecolor = 'gold'
p.facecolor = (1,.5,.5,.25)
p.facecolor = 0.25
p.fill = 'f'
print 'p.facecolor', type(p.facecolor), p.facecolor
print 'p.fill', type(p.fill), p.fill
if p.fill_: print 'fill'
else: print 'no fill'
if doprint:
 print
 print 'Patch'
 p.print_traits()
JDH

John, Tom,
I don't understand how generation of the identity transform for each 
Artist instance could possibly be a significant overall slowdown; it 
should be very fast, and only a small part of the time required to 
actually do anything useful with an Artist instance. I am wondering 
whether this could be a problem with the profiler, not a genuine slowdown.
Eric
John Hunter wrote:
>>>>>> "Tom" == Tom Denniston <tom...@al...> writes:
> 
> Tom> I've been profiling some of my code which builds many
> Tom> somewhat complex graphs. I've noticed that it spends almost
> Tom> all it's time in the __init__ of the artist class. The time
> Tom> there is almost entirely spent on calling identity_transform
> Tom> which builds a SeperableTransform that does no
> Tom> transforming--from what I can tell--which is consistent with
> Tom> the name. The identity transform function buid a bunch of
> Tom> other objects all of which are the same each time. My
> Tom> question is, does it really need to build all these objects
> Tom> over and over again. Given that Artist's __init__ is called
> Tom> by so many things wouldn't it be better to have some static
> Tom> constants to define these default transformation functions?
> Tom> Am I missing something subtle or would this be an
> Tom> improvement?
> 
> I'm hesitant to make a single (shared) identity transform since
> transforms are mutable. But since most objects to not use the
> identity_transform but rather a custom one, we can create it
> lazily. I've implemented these changes in svn. Each artist (as
> before) has a _transform instance but now it defaults to None. Then
> in get_transform
> 
> def get_transform(self):
> 'return the Transformation instance used by this artist'
> if self._transform is None:
> self._transform = identity_transform()
> return self._transform
> 
> The harder part was modifying all of the derived classes that were
> using the _transform attr directly -- all these had to be ported to
> use get_transform instead. The changes are documented in API_CHANGES.
> 
> See if it speeds up your code -- it didn't make an appreciable change
> to backend_driver.
> 
> Note the artist constructor shouldn't be a bottleneck in your python
> script. If it is, you are probably creating lots-o-artists and you
> might be able to use a collection instead. Eg, if you are making
> hundreds or thousands of calls to plot and creating a comparable
> number of Line2D artists, use a LineCollection instead.
> 
> But if you are still experiencing a problem and the changes I made to
> svn don't help (eg if you are creating lots of objects that do require
> the default identity_transform), you can experiment with using a
> single cached identity_transform. Something like
> 
> import matplotlib.artist
> 
> _cached_transform = matplotlib.artist.identity_transform()
> def my_identity_transform():
> return _cached_transform
> matplotlib.artist.identity_transform = my_identity_transform
> 
> # import the rest of mpl here
> 
> 
> 
> Hope this helps...
> 
> JDH
> 
> -------------------------------------------------------------------------
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John Hunter wrote:
> I'm hesitant to make a single (shared) identity transform since
> transforms are mutable.
Couldn't you make one that was immutable (is that possible in Python)? 
Or even just have a convention that you don't mutate the identity 
transform (though it could be way to late for that now!), kind of like 
how we all no not to assign anything else to the name "None".
> The harder part was modifying all of the derived classes that were
> using the _transform attr directly -- all these had to be ported to
> use get_transform instead.
This sounds like a job for properties! make _transform a property, and 
code that gets and sets it directly should still work. though People 
that were accessing an underscored name directly should expect this kind 
of problem.
-Chris
-- 
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
Chr...@no...

>>>>> "Eric" == Eric Emsellem <ems...@ob...> writes:
 Eric> Hi, I am trying to overplot symbols on a region filled (with
 Eric> pale grey color) between two curves. For some reason the
 Eric> filled region is always ON TOP of the symbols so that I
 Eric> don't see them..
 Eric> (I wanted to use transparency with alpha, but then it is to
 Eric> build a postscript figure which does not support
 Eric> transparency, so this requires me to first plot the filled
 Eric> region and then overplot the symbols...)
 Eric> here is an example:
 Eric> sampVS = arange(0.,1.,0.02) x = concatenate(
 Eric> (sampVS,sampVS[::-1]) ) alpha1 = 0.98486328 alpha2 =
 Eric> 1.28486328 y1 = alpha1 * sampVS / sqrt(1.+(alpha1 *
 Eric> sampVS)**2) y2 = alpha2 * sampVS / sqrt(1.+(alpha2 *
 Eric> sampVS)**2) y = concatenate( (y1,y2[::-1]) ) p = fill(x, y,
 Eric> facecolor=(0.9,0.9,0.9)) scatter([0.4],[0.4])
 Eric> ==> the symbol is hidden behind the filled region although
 Eric> it is plotted afterwards...
scatter (a PatchCollection) and fill (a Polygon) both have a zorder of
1, which means they are drawn at the bottom of the draw hierarchy. We
take all the artists, sort them by zorder, and draw them in order.
You should set the zorder of your scatter to be higher than the zorder
of your fill. Eg
 poly = fill(....)
 col = scatter(...)
 col.set_zorder( 1.1 * poly.get_zorder() )
See also examples/zorder_demo.py
JDH

Hi,
I am trying to overplot symbols on a region filled (with pale grey
color) between two curves.
For some reason the filled region is always ON TOP of the symbols so
that I don't see them..
(I wanted to use transparency with alpha, but then it is to build a
postscript figure which does not support transparency, so this requires
me to first plot the filled region and then overplot the symbols...)
here is an example:
sampVS = arange(0.,1.,0.02) 
x = concatenate( (sampVS,sampVS[::-1]) )
alpha1 = 0.98486328
alpha2 = 1.28486328
y1 = alpha1 * sampVS / sqrt(1.+(alpha1 * sampVS)**2)
y2 = alpha2 * sampVS / sqrt(1.+(alpha2 * sampVS)**2)
y = concatenate( (y1,y2[::-1]) )
p = fill(x, y, facecolor=(0.9,0.9,0.9))
scatter([0.4],[0.4])
==> the symbol is hidden behind the filled region although it is plotted
afterwards...
thanks for any input here!!
Eric
-- 
====================================================================
Eric Emsellem ems...@ob...
 Centre de Recherche Astrophysique de Lyon
9 av. Charles-Andre tel: +33 (0)4 78 86 83 84
69561 Saint-Genis Laval Cedex fax: +33 (0)4 78 86 83 86
France http://www-obs.univ-lyon1.fr/eric.emsellem
====================================================================

>>>>> "Tom" == Tom Denniston <tom...@al...> writes:
 Tom> I've been profiling some of my code which builds many
 Tom> somewhat complex graphs. I've noticed that it spends almost
 Tom> all it's time in the __init__ of the artist class. The time
 Tom> there is almost entirely spent on calling identity_transform
 Tom> which builds a SeperableTransform that does no
 Tom> transforming--from what I can tell--which is consistent with
 Tom> the name. The identity transform function buid a bunch of
 Tom> other objects all of which are the same each time. My
 Tom> question is, does it really need to build all these objects
 Tom> over and over again. Given that Artist's __init__ is called
 Tom> by so many things wouldn't it be better to have some static
 Tom> constants to define these default transformation functions?
 Tom> Am I missing something subtle or would this be an
 Tom> improvement?
I'm hesitant to make a single (shared) identity transform since
transforms are mutable. But since most objects to not use the
identity_transform but rather a custom one, we can create it
lazily. I've implemented these changes in svn. Each artist (as
before) has a _transform instance but now it defaults to None. Then
in get_transform
 def get_transform(self):
 'return the Transformation instance used by this artist'
 if self._transform is None:
 self._transform = identity_transform()
 return self._transform
The harder part was modifying all of the derived classes that were
using the _transform attr directly -- all these had to be ported to
use get_transform instead. The changes are documented in API_CHANGES.
See if it speeds up your code -- it didn't make an appreciable change
to backend_driver.
Note the artist constructor shouldn't be a bottleneck in your python
script. If it is, you are probably creating lots-o-artists and you
might be able to use a collection instead. Eg, if you are making
hundreds or thousands of calls to plot and creating a comparable
number of Line2D artists, use a LineCollection instead.
But if you are still experiencing a problem and the changes I made to
svn don't help (eg if you are creating lots of objects that do require
the default identity_transform), you can experiment with using a
single cached identity_transform. Something like
import matplotlib.artist
_cached_transform = matplotlib.artist.identity_transform()
def my_identity_transform():
 return _cached_transform
matplotlib.artist.identity_transform = my_identity_transform
# import the rest of mpl here
Hope this helps...
JDH

I've been profiling some of my code which builds many somewhat complex
graphs. I've noticed that it spends almost all it's time in the
__init__ of the artist class. The time there is almost entirely spent
on calling identity_transform which builds a SeperableTransform that
does no transforming--from what I can tell--which is consistent with
the name. The identity transform function buid a bunch of other
objects all of which are the same each time. My question is, does it
really need to build all these objects over and over again. Given
that Artist's __init__ is called by so many things wouldn't it be
better to have some static constants to define these default
transformation functions? Am I missing something subtle or would this
be an improvement?
What do people think?
def zero(): return Value(0)
def one() : return Value(1)
def origin():
 return Point( zero(), zero() )
def unit_bbox():
 """
 Get a 0,0 -> 1,1 Bbox instance
 """
 return Bbox( origin(), Point( one(), one() ) )
def identity_affine():
 """
 Get an affine transformation that maps x,y -> x,y
 """
 return Affine(one(), zero(), zero(), one(), zero(), zero())
def identity_transform():
 """
 Get an affine transformation that maps x,y -> x,y
 """
 return SeparableTransformation(unit_bbox(), unit_bbox(),
 Func(IDENTITY),
 Func(IDENTITY))

Piter_ wrote:
> If I start python (2.3).
> 
> >from pylab import *
> plot([1,2,3])
> nothing happens.
what if you then type:
show()
-Chris
-- 
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
Chr...@no...

Hi John,
* John Hunter
 <jdh...@ac...>
wrote:
>>>>>> "Fabian" == Fabian Braennstroem <f.b...@gm...> writes:
>
> >> I am trying to install matplotlib 0.87.7 with my newly separate
> >> installed python 2.5. For this I installed 'pygtk 2.4.1' and
> >> numpy 1.0 using this python 2.5 installation. Now, running
> >> 'python2.5 setup.py build' I get this error:
> >> 
> >> ... /usr/include/pygtk-2.0/pygobject.h:140: error: expected
> >> `,' or `...' before "typename"
>
> >> it seems, that matplotlib tries to use the old installed pygtk
> >> version; the new one is located in /usr/local/include/...
>
> Yes, this is the old pygtk bug covered in this FAQ
>
> http://matplotlib.sourceforge.net/faq.html#PYGTK24
Sorry, I did not see that ... thanks!
>
> maptlotlib gets its gtk configuration from the pkg-config commands, eg
>
> > pkg-config --cflags-only-I gtk+-2.0
>
> make sure your pkg-config is picking up the new pygtk you have
> installed, and if not set the PKG_CONFIG_PATH environment variable.
> See 'man pkg-config' for more details.
>
> Fabian> from matplotlib.pylab import * File
> Fabian> "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/pylab.py",
> Fabian> line 199, in <module> import mlab #so I can override hist,
> Fabian> psd, etc... File
> Fabian> "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/mlab.py",
> Fabian> line 6 4, in <module> import nxutils File
> Fabian> "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/nxutils.py",
> Fabian> lin e 17, in <module> from matplotlib._ns_nxutils import *
> Fabian> ImportError: No module named _ns_nxutils
> >>>> import numpy
>
> It appears you did not have numpy installed when you built
> matplotlib. Grab numpy-1.0 from http://numpy.scipy.org and install it
> (it's an easy install compared to mpl). Then rebuild and reinstall
> matplotlib and you should be good to go.
The numpy module is actually working (at least I could do an
'import numpy' without any response and was installed
before the matplotlib!? I try it again ...
Thanks and Greetings!
 Fabian

>>>>> "Fabian" == Fabian Braennstroem <f.b...@gm...> writes:
 >> I am trying to install matplotlib 0.87.7 with my newly separate
 >> installed python 2.5. For this I installed 'pygtk 2.4.1' and
 >> numpy 1.0 using this python 2.5 installation. Now, running
 >> 'python2.5 setup.py build' I get this error:
 >> 
 >> ... /usr/include/pygtk-2.0/pygobject.h:140: error: expected
 >> `,' or `...' before "typename"
 >> it seems, that matplotlib tries to use the old installed pygtk
 >> version; the new one is located in /usr/local/include/...
Yes, this is the old pygtk bug covered in this FAQ
 http://matplotlib.sourceforge.net/faq.html#PYGTK24
maptlotlib gets its gtk configuration from the pkg-config commands, eg
 > pkg-config --cflags-only-I gtk+-2.0
make sure your pkg-config is picking up the new pygtk you have
installed, and if not set the PKG_CONFIG_PATH environment variable.
See 'man pkg-config' for more details.
 Fabian> from matplotlib.pylab import * File
 Fabian> "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/pylab.py",
 Fabian> line 199, in <module> import mlab #so I can override hist,
 Fabian> psd, etc... File
 Fabian> "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/mlab.py",
 Fabian> line 6 4, in <module> import nxutils File
 Fabian> "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/nxutils.py",
 Fabian> lin e 17, in <module> from matplotlib._ns_nxutils import *
 Fabian> ImportError: No module named _ns_nxutils
 >>>> import numpy
It appears you did not have numpy installed when you built
matplotlib. Grab numpy-1.0 from http://numpy.scipy.org and install it
(it's an easy install compared to mpl). Then rebuild and reinstall
matplotlib and you should be good to go.
JDH

>>>>> "Piter" == Piter <x....@gm...> writes:
 Piter> Hi all. I am new user of matplot-lib and Python. I try to
 Piter> find replacement for matlab. Now I use Debian-testing but
 Piter> my experience with it is little. I have reinstalled system
 Piter> few days ago and matplotlib is not working now. If I start
 Piter> python (2.3).
 >> from pylab import *
 Piter> plot([1,2,3]) nothing happens.
 Piter> from IDLE it does not work to.
To run matplotlib from idle, you need to make the following changes to
your matplotlibrc file
backend : TkAgg
interactive : True
See http: //matplotlib.sourceforge.net/matplotlibrc for details on the
rc file and http://matplotlib.sourceforge.net/interactive.html for an
explanation of what these settings mean.
JDH

>>>>> "Brent" == Brent Fillery <bfi...@me...> writes:
 Brent> Hi All
 Brent> I am new to Matplotlib, and was wondering if anybody knew
 Brent> of an easy way to construct a dropline from a data point in
 Brent> a plot to the x axis, i.e. a vertical line from (x1,y1) to
 Brent> (x1,0)?
 ax.plot((x1, x1), (y1, 0), linestyle='-', color='black', linewidth=2)
should do it... There are some helper functions vline and
axvline you may want to look at
http://matplotlib.sourceforge.net/matplotlib.pylab.html#-axvline
http://matplotlib.sourceforge.net/matplotlib.pylab.html#-vline
The first will draw a vertical line that spans the axes vertical
extent regardless of zoom level, and the second simply draws a
vertical line at a given x from y1 to y2. vline supports many
vertical lines and for a single one as in your example, it's easy
enough to just use plot.
JDH

Hi all.
I am new user of matplot-lib and Python. I try to find replacement for
matlab.
Now I use Debian-testing but my experience with it is little.
I have reinstalled system few days ago and matplotlib is not working now.
If I start python (2.3).
>from pylab import *
plot([1,2,3])
nothing happens.
from IDLE
it does not work to.
if i run ipython -pylab
It works
How can I connect matplotlib to IDLE, or something similar.
Thanks.
Petro

Again, the problem with the sample you supply is that you are making 2-D 
arrays where what you need are 1-D arrays. Simply flattening y and pred 
before using them makes the script work fine, as attached. Or make them 
1-D in the first place.
Eric
Giorgio Luciano wrote:
> Thanks to all for the replies :)
> I used a tuple to solve the problem because I dind't manage to reshape 
> my array since it comes from a previous slicing, but not it seems to work.
> Is it the same problem because this doesn't work ?
> 
> from pylab import *
> y=array([[ 1.02], [ 1.05], [ 1.03], [ 0.99], [ 0.97], [ 0.95], [ 1. ], 
> [ 0.93], [ 1. ], [ 1. ], [ 0.98], [ 0.98], [ 0.94], [ 0.94], [ 
> 0.96], [ 0.92], [ 1.01], [ 0.96], [ 0.99], [ 0.96], [ 1.03], [ 
> 0.91], [ 0.99], [ 0.98], [ 1. ], [ 0.98], [ 0.96]])
> pred=array([[ 1.02875 ], [ 1.03125 ], [ 1.02291667], [ 0.99541667], 
> [ 0.96458333], [ 0.93625 ], [ 0.99375 ], [ 0.93708333], [ 1.00125 
> ], [ 1.01875 ], [ 0.98541667], [ 0.97291667],
> [ 0.94708333], [ 0.93458333], [ 0.96625 ], [ 0.92375 ], 
> [ 1.005 ], [ 0.965 ], [ 0.98333333], [ 0.96666667], [ 
> 1.02666667], [ 0.91333333], [ 1.005 ], [ 0.965 ], [ 0.98 ],
> [ 0.98 ], [ 0.98 ]])
> figure(2)
> r=27
> p2=plot(y,pred,'bo')
> t1=arange(1,r+1)
> for t1 in arange(1,r+1):
> text(y[t1-1], pred[t1-1], str(t1))
> show()
> ###### End Plot 2
> 
> and gives this error ??Exception in Tkinter callback
> Traceback (most recent call last):
> File "C:\Python24\lib\lib-tk\Tkinter.py", line 1345, in __call__
> return self.func(*args)
> File 
> "C:\Python24\Lib\site-packages\matplotlib\backends\backend_tkagg.py", 
> line 151, in resize
> self.show()
> File 
> "C:\Python24\Lib\site-packages\matplotlib\backends\backend_tkagg.py", 
> line 154, in draw
> FigureCanvasAgg.draw(self)
> File 
> "C:\Python24\Lib\site-packages\matplotlib\backends\backend_agg.py", line 
> 392, in draw
> self.figure.draw(renderer)
> File "C:\Python24\Lib\site-packages\matplotlib\figure.py", line 545, 
> in draw
> for a in self.axes: a.draw(renderer)
> File "C:\Python24\Lib\site-packages\matplotlib\axes.py", line 1067, in 
> draw
> a.draw(renderer)
> File "C:\Python24\Lib\site-packages\matplotlib\text.py", line 340, in draw
> bbox, info = self._get_layout(renderer)
> File "C:\Python24\Lib\site-packages\matplotlib\text.py", line 168, in 
> _get_layout
> if self.cached.has_key(key): return self.cached[key]
> TypeError: unhashable type
> 
> Thanks to all community :)
> Giorgio

Thanks to all for the replies :)
I used a tuple to solve the problem because I dind't manage to reshape 
my array since it comes from a previous slicing, but not it seems to work.
Is it the same problem because this doesn't work ?
from pylab import *
y=array([[ 1.02], [ 1.05], [ 1.03], [ 0.99], [ 0.97], [ 0.95], [ 1. ], 
[ 0.93], [ 1. ], [ 1. ], [ 0.98], [ 0.98], [ 0.94], [ 0.94], [ 
0.96], [ 0.92], [ 1.01], [ 0.96], [ 0.99], [ 0.96], [ 1.03], [ 
0.91], [ 0.99], [ 0.98], [ 1. ], [ 0.98], [ 0.96]])
pred=array([[ 1.02875 ], [ 1.03125 ], [ 1.02291667], [ 0.99541667], 
[ 0.96458333], [ 0.93625 ], [ 0.99375 ], [ 0.93708333], [ 1.00125 
], [ 1.01875 ], [ 0.98541667], [ 0.97291667],
 [ 0.94708333], [ 0.93458333], [ 0.96625 ], [ 0.92375 ], 
[ 1.005 ], [ 0.965 ], [ 0.98333333], [ 0.96666667], [ 
1.02666667], [ 0.91333333], [ 1.005 ], [ 0.965 ], [ 0.98 ],
 [ 0.98 ], [ 0.98 ]])
figure(2)
r=27
p2=plot(y,pred,'bo')
t1=arange(1,r+1)
for t1 in arange(1,r+1):
 text(y[t1-1], pred[t1-1], str(t1))
show()
###### End Plot 2
and gives this error ??Exception in Tkinter callback
Traceback (most recent call last):
 File "C:\Python24\lib\lib-tk\Tkinter.py", line 1345, in __call__
 return self.func(*args)
 File 
"C:\Python24\Lib\site-packages\matplotlib\backends\backend_tkagg.py", 
line 151, in resize
 self.show()
 File 
"C:\Python24\Lib\site-packages\matplotlib\backends\backend_tkagg.py", 
line 154, in draw
 FigureCanvasAgg.draw(self)
 File 
"C:\Python24\Lib\site-packages\matplotlib\backends\backend_agg.py", line 
392, in draw
 self.figure.draw(renderer)
 File "C:\Python24\Lib\site-packages\matplotlib\figure.py", line 545, 
in draw
 for a in self.axes: a.draw(renderer)
 File "C:\Python24\Lib\site-packages\matplotlib\axes.py", line 1067, in 
draw
 a.draw(renderer)
 File "C:\Python24\Lib\site-packages\matplotlib\text.py", line 340, in draw
 bbox, info = self._get_layout(renderer)
 File "C:\Python24\Lib\site-packages\matplotlib\text.py", line 168, in 
_get_layout
 if self.cached.has_key(key): return self.cached[key]
TypeError: unhashable type
Thanks to all community :)
Giorgio

Hi,
me again :-)
* Fabian Braennstroem
 <f.b...@gm...> wrote:
> Hi,
>
> I am trying to install matplotlib 0.87.7 with my newly
> separate installed python 2.5. For this I installed 'pygtk
> 2.4.1' and numpy 1.0 using this python 2.5 installation.
> Now, running 'python2.5 setup.py build' I get this error:
>
> ...
> /usr/include/pygtk-2.0/pygobject.h:140: error: expected `,' or `...' before "typename"
> /usr/include/pygtk-2.0/pygobject.h:147: error: expected `,' or `...' before "typename"
> ./CXX/Extensions.hxx: In constructor `Py::PythonExtension<T>::PythonExtension() [with T = BufferRegion]':
> src/_backend_agg.h:50: instantiated from here
> ./CXX/Extensions.hxx:477: warning: right-hand operand of comma has no effect
> ./CXX/Extensions.hxx: In constructor `Py::PythonExtension<T>::PythonExtension() [with T = LazyValue]':
> src/_transforms.h:57: instantiated from here
> ./CXX/Extensions.hxx:477: warning: right-hand operand of comma has no effect
> ./CXX/Extensions.hxx: In constructor `Py::PythonExtension<T>::PythonExtension() [with T = Func]':
> src/_transforms.h:379: instantiated from here
> ./CXX/Extensions.hxx:477: warning: right-hand operand of comma has no effect
> ./CXX/Extensions.hxx: In constructor `Py::PythonExtension<T>::PythonExtension() [with T = FuncXY]':
> src/_transforms.h:466: instantiated from here
> ./CXX/Extensions.hxx:477: warning: right-hand operand of comma has no effect
> ./CXX/Extensions.hxx: In constructor `Py::PythonExtension<T>::PythonExtension() [with T = Transformation]':
> src/_transforms.h:538: instantiated from here
> ./CXX/Extensions.hxx:477: warning: right-hand operand of comma has no effect
> error: Command "gcc -pthread -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC -I/usr/local/include -I/usr/include -I. -Isrc -Iswig -Iagg23/include -I. -I/usr/local/include -I/usr/include -I. -I/usr/local/include/freetype2 -I/usr/include/freetype2 -I./freetype2 -Isrc/freetype2 -Iswig/freetype2 -Iagg23/include/freetype2 -I./freetype2 -I/usr/local/include/freetype2 -I/usr/include/freetype2 -I./freetype2 -I/usr/local/include -I/usr/include -I. -I/usr/include/pygtk-2.0 -I/usr/include/glib-2.0 -I/usr/lib/glib-2.0/include -I/usr/include/gtk-2.0 -I/usr/lib/gtk-2.0/include -I/usr/X11R6/include -I/usr/include/atk-1.0 -I/usr/include/pango-1.0 -I/usr/include/freetype2 -I/usr/include/freetype2/config -I/usr/include/glib-2.0 -I/usr/lib/glib-2.0/include -I/opt/python-2.5/include/python2.5 -c src/_gtkagg.cpp -o build/temp.linux-i686-2.5/src/_gtkagg.o" failed with exit status 1
>
> it seems, that matplotlib tries to use the old installed pygtk version; the new
> one is located in /usr/local/include/...
I could fix this problem with setting:
BUILD_AGG = 0
BUILD_GTKAGG = 0
BUILD_GTK = 1
but now, I get the following problem:
node1~$ python2.5 [05 Dec 7:45am]
Python 2.5 (r25:51908, Dec 2 2006, 19:02:24) 
[GCC 3.4.5 20051201 (Red Hat 3.4.5-2)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import pylab
The import of the numpy version of the nxutils module,
_nsnxutils, failed. This is is either because numpy was
unavailable when matplotlib was compiled, because a dependency of
_nsnxutils could not be satisfied, or because the build flag for
this module was turned off in setup.py. If it appears that
_nsnxutils was not built, make sure you have a working copy of
numpy and then re-install matplotlib. Otherwise, the following
traceback gives more details:
Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
 File "/opt/python-2.5//lib/python2.5/site-packages/pylab.py", line 1, in <modu
le>
 from matplotlib.pylab import *
 File "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/pylab.py", line 
199, in <module>
 import mlab #so I can override hist, psd, etc...
 File "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/mlab.py", line 6
4, in <module>
 import nxutils
 File "/opt/python-2.5//lib/python2.5/site-packages/matplotlib/nxutils.py", lin
e 17, in <module>
 from matplotlib._ns_nxutils import *
ImportError: No module named _ns_nxutils
>>> import numpy
>>> 
I checked the setup script; it says:
# these are not optional
BUILD_FT2FONT = 1
BUILD_CONTOUR = 1
BUILD_NXUTILS = 1
so _nxutils should be installed and numpy loads without any problems!? Does anybody have an idea?
Greetings!
 Fabian

That worked. Thanx a lot Eric. I just had to also add 
interpolation='nearest' in imshow() and it worked just like matshow did.
>From: Eric Firing <ef...@ha...>
>To: TheSaint 555 <the...@ho...>
>CC: mat...@li...
>Subject: Re: [Matplotlib-users] subplots of matshow
>Date: 2006年12月04日 14:42:20 -1000
>
>def matshow(*args,**kw):
> """Display an array as a matrix in a new figure window.
>
>
>Matshow simply is not designed to work with subplots; it is a wrapper 
>around imshow() that creates a new figure. You should be able to do what 
>you want by using imshow() directly in place of matshow with something like 
>this:
>
>nr, nc = Z.shape
>extent = [-0.5, nc-0.5, nr-0.5, -0.5]
>imshow(Z, extent=extent, origin='upper')
>
>This should display the matrix with the same orientation as it has when 
>printed, and with the axis ticks matching the indices.
>
>Change or add kwargs to imshow as needed. aspect is 'equal' by default, 
>which may or may not be what you want, but it is part of what matshow tries 
>to do if the matrix aspect ratio is not too far from unity.
>
>Eric
>
>
>
>
>TheSaint 555 wrote:
>>I am trying to create subplots with matshow. However, my code seems to be 
>>displaying only the last matshow image and two blank plots in separate 
>>figures. Can someone tell me what I am doing wrong?
>>
>>from matplotlib.pylab import *
>>
>>def SliceMat(N, i):
>> slice = zeros( (N, N) )
>> for j in range(N):
>> for k in range(N):
>> val = 0 # black
>> if(i>j>k and ((i+j+k)%3==1)):
>> val=1 # red
>> if(j>k>i and ((i+j+k)%3==2)):
>> val=2 # yellow
>> if (k>i>j and ((i+j+k)%3==0)):
>> val=3 # white
>> slice[j,k] = val
>> return slice
>>
>>N=8
>>
>>
>>subplot(121)
>>slice = SliceMat(N, 2)
>>matshow(slice, cmap=cm.hot, origin='lower')
>>
>>
>>
>>subplot(122)
>>slice = SliceMat(N, 5)
>>matshow(slice, cmap=cm.hot, origin='lower')
>>
>>show()
>>
>>_________________________________________________________________
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def matshow(*args,**kw):
 """Display an array as a matrix in a new figure window.
Matshow simply is not designed to work with subplots; it is a wrapper 
around imshow() that creates a new figure. You should be able to do 
what you want by using imshow() directly in place of matshow with 
something like this:
nr, nc = Z.shape
extent = [-0.5, nc-0.5, nr-0.5, -0.5]
imshow(Z, extent=extent, origin='upper')
This should display the matrix with the same orientation as it has when 
printed, and with the axis ticks matching the indices.
Change or add kwargs to imshow as needed. aspect is 'equal' by default, 
which may or may not be what you want, but it is part of what matshow 
tries to do if the matrix aspect ratio is not too far from unity.
Eric
TheSaint 555 wrote:
> I am trying to create subplots with matshow. However, my code seems to be 
> displaying only the last matshow image and two blank plots in separate 
> figures. Can someone tell me what I am doing wrong?
> 
> from matplotlib.pylab import *
> 
> def SliceMat(N, i):
> slice = zeros( (N, N) )
> for j in range(N):
> for k in range(N):
> val = 0 # black
> if(i>j>k and ((i+j+k)%3==1)):
> val=1 # red
> if(j>k>i and ((i+j+k)%3==2)):
> val=2 # yellow
> if (k>i>j and ((i+j+k)%3==0)):
> val=3 # white
> slice[j,k] = val
> return slice
> 
> N=8
> 
> 
> subplot(121)
> slice = SliceMat(N, 2)
> matshow(slice, cmap=cm.hot, origin='lower')
> 
> 
> 
> subplot(122)
> slice = SliceMat(N, 5)
> matshow(slice, cmap=cm.hot, origin='lower')
> 
> show()
> 
> _________________________________________________________________
> Connect with your friends who use Yahoo! Messenger with Voice. Click! 
> http://www.msnspecials.in/wlmyahoo/index.asp
> 
> 
> -------------------------------------------------------------------------
> Take Surveys. Earn Cash. Influence the Future of IT
> Join SourceForge.net's Techsay panel and you'll get the chance to share your
> opinions on IT & business topics through brief surveys - and earn cash
> http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV
> _______________________________________________
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> Mat...@li...
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